Combined ensemble
63.5%
Accuracy on 285 holdout games
AUC-ROC: Not reported
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Transparent training, accuracy, market, and methodology reporting
Model construction and transparency
See how game data becomes a probability, why three models are combined, and which inputs the tree-based component used most. Construction details explain the system; they do not establish future performance.
The shortest path from source data to a published home-win probability.
Prediction assembly line
How one final probability is constructed and then evaluated.
01 · Source
Historical team, matchup, availability, and game-context inputs.
02 · Transform
Validated columns form the candidate pool before component-specific selection.
03 · Three lenses
Tree-based and regularized linear models estimate home-win probability.
04 · Run config
Configured contribution shares combine the three component probabilities.
05 · Published output
One final home-win probability becomes the model prediction shown to visitors.
Holdout · not used for training
285 games test the completed pipeline
Evaluation measures this historical sample; it does not guarantee future performance.
Component roles, same-sample evaluation, configured weights, and agreement coverage.
Each component sees the same game inputs through a different mathematical lens. Their home-win probabilities are combined with configured weights. The weights are implementation inputs, not proof that one model is better.
63.5%
Accuracy on 285 holdout games
AUC-ROC: Not reported
Pattern finder
Finds nonlinear patterns and interactions in the shared feature matrix.
Signal reducer
Fits a regularized linear view that can reduce the influence of redundant inputs.
Probability lens
Provides a simpler probability estimate from linear relationships.
All reported accuracy values above are directly comparable only because they use the same holdout sample. A component scoring higher on this sample does not establish that it will remain better on future games.
Source: training-run configuration (legacy artifact).
QuantCup ensemble
63.5%
holdout accuracy
Stream length is a visual aid for configured contribution only; it does not represent model quality.
Agreement describes whether component picks pointed to the same team; it does not measure correctness.
of 285 comparable games
of 285 comparable games
excluded from agreement rates
Registered inputs are checked for configuration, availability, and selection before component-specific training matrices are built.
Candidate inputs
62
Linear models
42
Tree model
45
Selected union
45
Ranked evidence
45
Unavailable
0
Legacy artifact: 62 candidate inputs produced a 45-feature selected union, derived from component assignments and ranked XGBoost evidence. Future artifacts report these count scopes directly.
Feature category constellation
Node size represents the number of reported features, not importance.
Selected union
45
model features
The five highest source-ranked features in this run.
rolling_8g_points_for_diff
#1
source rank
rolling_16g_epa_offense_diff
#2
source rank
rolling_4g_win_rate_diff
#3
source rank
rolling_16g_point_diff_diff
#4
source rank
high_wind
#5
source rank